---
license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ast-finetuned-audioset-10-10-0.4593-finetuned-gunshot
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# ast-finetuned-audioset-10-10-0.4593-finetuned-gunshot

This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co./MIT/ast-finetuned-audioset-10-10-0.4593) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8955
- Accuracy: 0.7647

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.771         | 1.0   | 341  | 1.4439          | 0.6294   |
| 3.4687        | 2.0   | 682  | 1.2804          | 0.6824   |
| 0.7887        | 3.0   | 1023 | 0.5085          | 0.7412   |
| 0.4093        | 4.0   | 1364 | 0.4299          | 0.7882   |
| 0.1765        | 5.0   | 1705 | 0.3885          | 0.8471   |
| 0.1055        | 6.0   | 2046 | 0.4319          | 0.7941   |
| 0.1341        | 7.0   | 2387 | 0.4773          | 0.8      |
| 0.0722        | 8.0   | 2728 | 0.8647          | 0.7412   |
| 0.156         | 9.0   | 3069 | 0.9191          | 0.7647   |
| 0.0377        | 10.0  | 3410 | 0.8955          | 0.7647   |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.0.0
- Datasets 2.15.1.dev0
- Tokenizers 0.15.0